There are a variety of previous approaches to detecting commercials in a television broadcast. However, previous approaches suffer from a flaw in that they act as relatively simple finite state machines with little or no error recovery. Previous approaches sometimes make an erroneous decision regarding a commercial location which only becomes apparent by considering data far ahead or after the commercial location in time. However, since previous approaches don't consider such data, information regarding the erroneous decision is ignored and the error remains uncorrected.
Merlino et al. of the MITRE corporation describe a multiple-cue-based method for segmenting news programs, including finding the commercial breaks. The Merlino et al. method uses black frames, audio silence and blank closed-captioning to find commercials, R. Lienhart et al. of the University of Mannheim also describe a multiple-cue-based system for detecting commercials. The Lienhart et al. method uses black frames, scene cuts and a measure of motion in a visual recording to detect commercials. The Informedia project at Carnegie-Mellon University used black frames, scene cuts and lapses in closed-captioning to detect commercials. Additionally, some VCRs come with commercial detection built in to the VCR. There are also a number of patents that describe methods for commercial detection, all of which use coincidences of black frames, audio silence and/or certain closed-captioning signals to detect commercials. For example, U.S. Pat. Nos. 4,319,286, 4,750,053, 4,390,904, 4,782,401 and 4,602,297 detect commercials based on these types of coincidences.
All of the previous approaches to commercial detection select commercial start or end times as the times at which some combination of cues, such as a black frame and an audio pause, coincide, with some optional restrictions. Typically, in previous approaches the decision as to whether or not a commercial starts at a particular time “t” is independent of the analogous decision for any other time in the audiovisual broadcast or recording. Previous approaches in which such complete independence does not exist use only a very limited dependence in which the decision at time “t” may be affected by whether or not a commercial was thought to start within some window of time [t−n, . . . , t] prior to the time “t”. Thus, in previous approaches, a commercial detection decision made at any time “t” in a broadcast or recording is not affected by parts of the broadcast or recording following time “t” and only sometimes is affected by limited parts (less than one minute) of the broadcast or recording immediately prior to time “t”. Further, none of the previous approaches have any sort of double-checking or error recovery; once a decision is made for time “t”, by whatever heuristic the approach uses, the decision remains unchanged no matter what happens in the broadcast or recording after time “t” and no matter what other decisions are made before or after time “t”. In summary, previous approaches to commercial detection make decisions as to commercial locations both time-locally and sequentially, i.e., only data from within a narrow time window about a particular time t is considered in making the decision as to whether a commercial starts or ends at that time t, and the decisions are made one at a time and are never reversed.